Submitted to: Journal of the American Water Resources Association
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/31/2006
Publication Date: 1/31/2007
Citation: Confesor, R.B., Whittaker, G.W. 2007. Automatic Calibration of Hydrologic Models with Multi-Objective Evolutionary Algorithm and Pareto Optimization . Journal of the American Water Resources Association.43:1-9.
Interpretive Summary: Large, complex simulation models like the Soil and Water Assessment Tool are increasing used in the analysis of the effects of agricultural production on the environment. For these models to be credible, they have to be calibrated by adjusting internal parameters until they can reproduce observed physical measurements, such as streamflow in a watershed. Calibration by an individual requires a great deal of specialized knowledge and time. This study applies a new method of calibration that requires no human intervention, and requires only a few hours to run. We apply it to the calibration of SWAT for the hydrology of the Calapooia watershed. The simulations produced by the calibrated model match the observed hydrologic data quite well, providing strong support for predictions made with the calibrated model. The calibrated model is now available for the analysis of decision and policy-making problems related to conflicting objectives of economics and environmental quality.
Technical Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade-offs between these objectives. The Pareto optimal set is achieved when no solution can be improved without degrading another one. This study investigated the application of multi-objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process-based, semi-distributed, and continuous hydrologic model. The non-dominated sorting genetic algorithm (NSGA-II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. One hundred thirty-nine parameters were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3-year period. The daily Nash-Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi-objective calibration of a complex watershed model was successfully implemented using Pareto ordering optimization and multi-objective evolutionary algorithm. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy-making problems related to conflicting objectives of economics and environmental quality.